肺小结节建模、检测及临床评价

A. Farag, J. Graham, H. Abdelmunim, S. Elshazly, M. Ei-Mogy, S. Ei-Mogy, R. Falk, A. Farag
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引用次数: 4

摘要

本文研究了利用主动外观建模(AAM)方法进行肺结节自动检测的模板建模过程。制定了模板匹配方法来计算AAM模板与输入肺CT切片之间的相似性评分,其目标是最大化不同图像像素处的相似性度量,以增加结节检测。模板匹配方法采用9个相似度度量来实现。在三个临床数据库上对生成的模型的鲁棒性进行了性能验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Small-size lung nodule modeling and detection with clinical evaluation
In this paper examination of the template modeling process using the Active Appearance Modeling (AAM) approach for automatic detection of lung nodules is investigated. A template matching approach is formulated to compute a similarity score between the AAM templates and the input lung CT slice, where the goal is to maximize the similarity measure at different image pixels to increase nodule detection. The template matching approach is implemented using nine similarity measures. Performance validation for the robustness of the generated models is tested on three clinical databases.
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